Performance and Energy Assessment of Last-Level Cache Replacement Policies

Pierre-Yves Péneau 1 David Novo 1 Florent Bruguier 1 Gilles Sassatelli 1 Abdoulaye Gamatié 1
1 ADAC - ADAptive Computing
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : The Last-Level Cache (LLC) is a critical component of the memory hierarchy which has a direct impact on performance. Whenever a data requested by a processor core is not found in the cache a transaction to the main memory is initiated, which results in both performance and energy penalties. Decreasing LLC miss rate therefore lowers external memory transactions which is beneficial both power and performance-wise. The cache replacement policy has a direct impact on the miss rate. It is responsible of data eviction of cache lines whenever the cache runs full. Thus, a good policy should evict data that will be re-used in a distant-future, and favour data that are likely to be accessed in the near-future. The most common cache replacement policy is the Least-Recently Used (LRU) strategy. It has been used for years and is cheaper in terms of hardware implementation. However, researchers have shown that LRU is not the most efficient policy from a performance point of view, and is further largely sub-optimal compared to the best theoretical strategy. In this paper, we analyze a number of cache replacement policies that have been proposed over the last decade and carry out evaluations reporting performance and energy.
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Communication dans un congrès
EDIS: Embedded & Distributed Systems, Dec 2017, Oran, Algeria. 1st international conference on Embedded & Distributed Systems, 2017, 〈https://sites.google.com/view/edis2017〉
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Pierre-Yves Péneau, David Novo, Florent Bruguier, Gilles Sassatelli, Abdoulaye Gamatié. Performance and Energy Assessment of Last-Level Cache Replacement Policies. EDIS: Embedded & Distributed Systems, Dec 2017, Oran, Algeria. 1st international conference on Embedded & Distributed Systems, 2017, 〈https://sites.google.com/view/edis2017〉. 〈lirmm-01651247〉

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